{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/NielsRogge/Transformers-Tutorials/blob/master/LLaVa/Fine_tune_LLaVa_on_a_custom_dataset_(with_PyTorch_Lightning).ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xTG2AJZT89qk"
      },
      "source": [
        "## Fine-tune LLaVa for document parsing (PDF -> JSON)\n",
        "\n",
        "In this notebook, we are going to fine-tune the [LLaVa](https://huggingface.co/docs/transformers/main/en/model_doc/llava) model for a document AI use case. LLaVa is one of the better open-source multimodal models at the time of writing (there's already a successor called [LLaVa-NeXT](https://huggingface.co/docs/transformers/main/en/model_doc/llava_next)). As we'll see, fine-tuning these various models is pretty similar as their API is mostly the same.\n",
        "\n",
        "The goal for the model in this notebook is to generate a JSON that contains key fields (like food items and their corresponding prices) from receipts. We will fine-tune LLaVa on the [CORD](https://huggingface.co/datasets/naver-clova-ix/cord-v2) dataset, which contains (receipt image, ground truth JSON) pairs.\n",
        "\n",
        "Sources:\n",
        "\n",
        "* LLaVa [documentation](https://huggingface.co/docs/transformers/main/en/model_doc/llava)\n",
        "* LLaVa [models on the hub](https://huggingface.co/llava-hf)\n",
        "\n",
        "Note: this notebook is a direct adaptation of my [Idefics2 notebook](https://github.com/NielsRogge/Transformers-Tutorials/blob/master/Idefics2/Fine_tune_Idefics2_for_JSON_extraction_use_cases_(PyTorch_Lightning).ipynb) for LLaVa."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Szf17AKL89qm"
      },
      "source": [
        "## Define variables\n",
        "\n",
        "We'll first set some variables useful througout this notebook."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "LJtnWc3b89qn"
      },
      "outputs": [],
      "source": [
        "MAX_LENGTH = 384\n",
        "MODEL_ID = \"llava-hf/llava-1.5-7b-hf\"\n",
        "REPO_ID = \"nielsr/llava-finetuning-demo\"\n",
        "WANDB_PROJECT = \"LLaVa\"\n",
        "WANDB_NAME = \"llava-demo-cord\""
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sqEY8CKq89qo"
      },
      "source": [
        "## Load dataset\n",
        "\n",
        "Let's start by loading the dataset from the hub. Here we use the [CORD](https://huggingface.co/datasets/naver-clova-ix/cord-v2) dataset, created by the [Donut](https://huggingface.co/docs/transformers/en/model_doc/donut) authors (Donut is another powerful - but slightly undertrained document AI model available in the Transformers library). CORD is an important benchmark for receipt understanding. The Donut authors have prepared it in a format that suits vision-language models: we're going to fine-tune it to generate the JSON given the image.\n",
        "\n",
        "If you want to load your own custom dataset, check out this guide: https://huggingface.co/docs/datasets/image_dataset."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "rsDFIa1u89qo",
        "outputId": "04706c10-de2c-4697-b967-9faf8c4aa143"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/home/niels/python_projects/transformers/env/lib/python3.8/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
            "  from .autonotebook import tqdm as notebook_tqdm\n"
          ]
        }
      ],
      "source": [
        "from datasets import load_dataset\n",
        "\n",
        "dataset = load_dataset(\"naver-clova-ix/cord-v2\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tRPAuOo489qo"
      },
      "source": [
        "Let's check out the dataset:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "0tNseDKK89qp",
        "outputId": "d34de83a-d20c-41f1-e8ec-77be559865d4"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "DatasetDict({\n",
              "    train: Dataset({\n",
              "        features: ['image', 'ground_truth'],\n",
              "        num_rows: 800\n",
              "    })\n",
              "    validation: Dataset({\n",
              "        features: ['image', 'ground_truth'],\n",
              "        num_rows: 100\n",
              "    })\n",
              "    test: Dataset({\n",
              "        features: ['image', 'ground_truth'],\n",
              "        num_rows: 100\n",
              "    })\n",
              "})"
            ]
          },
          "execution_count": 4,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "dataset"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FIlVNVpM89qp"
      },
      "source": [
        "As oftentimes, we get a `DatasetDict` which is a dictionary containing 3 splits, one for training, validation and testing. Each split has 2 features, an image and a corresponding ground truth.\n",
        "\n",
        " Let's check the first training example:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Z9dGYHGM89qp",
        "outputId": "f6b219ea-e43a-434a-853c-a3ad6a08b11b"
      },
      "outputs": [
        {
          "data": {
            "image/jpeg": 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",
            "image/png": 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",
            "text/plain": [
              "<PIL.Image.Image image mode=RGB size=259x388>"
            ]
          },
          "execution_count": 5,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "example = dataset['train'][0]\n",
        "image = example[\"image\"]\n",
        "# resize image for smaller displaying\n",
        "width, height = image.size\n",
        "image = image.resize((int(0.3*width), int(0.3*height)))\n",
        "image"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Yz2nYL9A89qp"
      },
      "source": [
        "Let's check the corresponding ground truth:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ubxkHK7x89qp",
        "outputId": "06225fb0-e2d9-4bca-a8b5-cf81921688c6"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "'{\"gt_parse\": {\"menu\": [{\"nm\": \"Nasi Campur Bali\", \"cnt\": \"1 x\", \"price\": \"75,000\"}, {\"nm\": \"Bbk Bengil Nasi\", \"cnt\": \"1 x\", \"price\": \"125,000\"}, {\"nm\": \"MilkShake Starwb\", \"cnt\": \"1 x\", \"price\": \"37,000\"}, {\"nm\": \"Ice Lemon Tea\", \"cnt\": \"1 x\", \"price\": \"24,000\"}, {\"nm\": \"Nasi Ayam Dewata\", \"cnt\": \"1 x\", \"price\": \"70,000\"}, {\"nm\": \"Free Ice Tea\", \"cnt\": \"3 x\", \"price\": \"0\"}, {\"nm\": \"Organic Green Sa\", \"cnt\": \"1 x\", \"price\": \"65,000\"}, {\"nm\": \"Ice Tea\", \"cnt\": \"1 x\", \"price\": \"18,000\"}, {\"nm\": \"Ice Orange\", \"cnt\": \"1 x\", \"price\": \"29,000\"}, {\"nm\": \"Ayam Suir Bali\", \"cnt\": \"1 x\", \"price\": \"85,000\"}, {\"nm\": \"Tahu Goreng\", \"cnt\": \"2 x\", \"price\": \"36,000\"}, {\"nm\": \"Tempe Goreng\", \"cnt\": \"2 x\", \"price\": \"36,000\"}, {\"nm\": \"Tahu Telor Asin\", \"cnt\": \"1 x\", \"price\": \"40,000.\"}, {\"nm\": \"Nasi Goreng Samb\", \"cnt\": \"1 x\", \"price\": \"70,000\"}, {\"nm\": \"Bbk Panggang Sam\", \"cnt\": \"3 x\", \"price\": \"366,000\"}, {\"nm\": \"Ayam Sambal Hija\", \"cnt\": \"1 x\", \"price\": \"92,000\"}, {\"nm\": \"Hot Tea\", \"cnt\": \"2 x\", \"price\": \"44,000\"}, {\"nm\": \"Ice Kopi\", \"cnt\": \"1 x\", \"price\": \"32,000\"}, {\"nm\": \"Tahu Telor Asin\", \"cnt\": \"1 x\", \"price\": \"40,000\"}, {\"nm\": \"Free Ice Tea\", \"cnt\": \"1 x\", \"price\": \"0\"}, {\"nm\": \"Bebek Street\", \"cnt\": \"1 x\", \"price\": \"44,000\"}, {\"nm\": \"Ice Tea Tawar\", \"cnt\": \"1 x\", \"price\": \"18,000\"}], \"sub_total\": {\"subtotal_price\": \"1,346,000\", \"service_price\": \"100,950\", \"tax_price\": \"144,695\", \"etc\": \"-45\"}, \"total\": {\"total_price\": \"1,591,600\"}}, \"meta\": {\"version\": \"2.0.0\", \"split\": \"train\", \"image_id\": 0, \"image_size\": {\"width\": 864, \"height\": 1296}}, \"valid_line\": [{\"words\": [{\"quad\": {\"x2\": 244, \"y3\": 390, \"x3\": 244, \"y4\": 390, \"x1\": 232, \"y1\": 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0, \"row_id\": 2179907, \"text\": \"Sam\"}], \"category\": \"menu.nm\", \"group_id\": 17, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 630, \"y3\": 742, \"x3\": 630, \"y4\": 742, \"x1\": 538, \"y1\": 716, \"x4\": 538, \"y2\": 716}, \"is_key\": 0, \"row_id\": 2179907, \"text\": \"366,000\"}], \"category\": \"menu.price\", \"group_id\": 17, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 254, \"y3\": 778, \"x3\": 254, \"y4\": 778, \"x1\": 242, \"y1\": 762, \"x4\": 242, \"y2\": 762}, \"is_key\": 0, \"row_id\": 2179908, \"text\": \"1\"}, {\"quad\": {\"x2\": 280, \"y3\": 778, \"x3\": 280, \"y4\": 778, \"x1\": 266, \"y1\": 764, \"x4\": 266, \"y2\": 764}, \"is_key\": 0, \"row_id\": 2179908, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 18, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 364, \"y3\": 778, \"x3\": 364, \"y4\": 778, \"x1\": 312, \"y1\": 754, \"x4\": 312, \"y2\": 754}, \"is_key\": 0, \"row_id\": 2179908, \"text\": \"Ayam\"}, {\"quad\": {\"x2\": 447, \"y3\": 771, \"x3\": 448, \"y4\": 774, \"x1\": 371, \"y1\": 750, \"x4\": 372, \"y2\": 747}, \"is_key\": 0, \"row_id\": 2179908, \"text\": \"Sambal\"}, {\"quad\": {\"x2\": 508, \"y3\": 772, \"x3\": 508, \"y4\": 772, \"x1\": 454, \"y1\": 746, \"x4\": 454, \"y2\": 746}, \"is_key\": 0, \"row_id\": 2179908, \"text\": \"Hija\"}], \"category\": \"menu.nm\", \"group_id\": 18, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 632, \"y3\": 768, \"x3\": 632, \"y4\": 768, \"x1\": 554, \"y1\": 742, \"x4\": 554, \"y2\": 742}, \"is_key\": 0, \"row_id\": 2179908, \"text\": \"92,000\"}], \"category\": \"menu.price\", \"group_id\": 18, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 254, \"y3\": 806, \"x3\": 254, \"y4\": 806, \"x1\": 236, \"y1\": 784, \"x4\": 236, \"y2\": 784}, \"is_key\": 0, \"row_id\": 2179909, \"text\": \"2\"}, {\"quad\": {\"x2\": 278, \"y3\": 804, \"x3\": 278, \"y4\": 804, \"x1\": 262, \"y1\": 788, \"x4\": 262, \"y2\": 788}, \"is_key\": 0, \"row_id\": 2179909, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 19, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 352, \"y3\": 802, \"x3\": 352, \"y4\": 802, \"x1\": 310, \"y1\": 780, \"x4\": 310, \"y2\": 780}, \"is_key\": 0, \"row_id\": 2179909, \"text\": \"Hot\"}, {\"quad\": {\"x2\": 400, \"y3\": 800, \"x3\": 400, \"y4\": 800, \"x1\": 358, \"y1\": 778, \"x4\": 358, \"y2\": 778}, \"is_key\": 0, \"row_id\": 2179909, \"text\": \"Tea\"}], \"category\": \"menu.nm\", \"group_id\": 19, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 634, \"y3\": 796, \"x3\": 634, \"y4\": 796, \"x1\": 554, \"y1\": 770, \"x4\": 554, \"y2\": 770}, \"is_key\": 0, \"row_id\": 2179909, \"text\": \"44,000\"}], \"category\": \"menu.price\", \"group_id\": 19, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 252, \"y3\": 834, \"x3\": 252, \"y4\": 834, \"x1\": 240, \"y1\": 816, \"x4\": 240, \"y2\": 816}, \"is_key\": 0, \"row_id\": 2179910, \"text\": \"1\"}, {\"quad\": {\"x2\": 278, \"y3\": 832, \"x3\": 278, \"y4\": 832, \"x1\": 262, \"y1\": 816, \"x4\": 262, \"y2\": 816}, \"is_key\": 0, \"row_id\": 2179910, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 20, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 352, \"y3\": 830, \"x3\": 352, \"y4\": 830, \"x1\": 312, \"y1\": 808, \"x4\": 312, \"y2\": 808}, \"is_key\": 0, \"row_id\": 2179910, \"text\": \"Ice\"}, {\"quad\": {\"x2\": 412, \"y3\": 830, \"x3\": 412, \"y4\": 830, \"x1\": 360, \"y1\": 804, \"x4\": 360, \"y2\": 804}, \"is_key\": 0, \"row_id\": 2179910, \"text\": \"Kopi\"}], \"category\": \"menu.nm\", \"group_id\": 20, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 636, \"y3\": 826, \"x3\": 636, \"y4\": 826, \"x1\": 556, \"y1\": 798, \"x4\": 556, \"y2\": 798}, \"is_key\": 0, \"row_id\": 2179910, \"text\": \"32,000\"}], \"category\": \"menu.price\", \"group_id\": 20, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 250, \"y3\": 862, \"x3\": 250, \"y4\": 862, \"x1\": 238, \"y1\": 844, \"x4\": 238, \"y2\": 844}, \"is_key\": 0, \"row_id\": 2179911, \"text\": \"1\"}, {\"quad\": {\"x2\": 276, \"y3\": 862, \"x3\": 276, \"y4\": 862, \"x1\": 260, \"y1\": 844, \"x4\": 260, \"y2\": 844}, \"is_key\": 0, \"row_id\": 2179911, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 21, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 364, \"y3\": 860, \"x3\": 364, \"y4\": 860, \"x1\": 310, \"y1\": 836, \"x4\": 310, \"y2\": 836}, \"is_key\": 0, \"row_id\": 2179911, \"text\": \"Tahu\"}, {\"quad\": {\"x2\": 438, \"y3\": 858, \"x3\": 438, \"y4\": 858, \"x1\": 372, \"y1\": 834, \"x4\": 372, \"y2\": 834}, \"is_key\": 0, \"row_id\": 2179911, \"text\": \"Telor\"}, {\"quad\": {\"x2\": 500, \"y3\": 854, \"x3\": 500, \"y4\": 854, \"x1\": 444, \"y1\": 832, \"x4\": 444, \"y2\": 832}, \"is_key\": 0, \"row_id\": 2179911, \"text\": \"Asin\"}], \"category\": \"menu.nm\", \"group_id\": 21, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 638, \"y3\": 854, \"x3\": 638, \"y4\": 854, \"x1\": 558, \"y1\": 826, \"x4\": 558, \"y2\": 826}, \"is_key\": 0, \"row_id\": 2179911, \"text\": \"40,000\"}], \"category\": \"menu.price\", \"group_id\": 21, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 250, \"y3\": 892, \"x3\": 250, \"y4\": 892, \"x1\": 238, \"y1\": 872, \"x4\": 238, \"y2\": 872}, \"is_key\": 0, \"row_id\": 2179912, \"text\": \"1\"}, {\"quad\": {\"x2\": 276, \"y3\": 890, \"x3\": 276, \"y4\": 890, \"x1\": 260, \"y1\": 872, \"x4\": 260, \"y2\": 872}, \"is_key\": 0, \"row_id\": 2179912, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 22, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 364, \"y3\": 888, \"x3\": 364, \"y4\": 888, \"x1\": 310, \"y1\": 866, \"x4\": 310, \"y2\": 866}, \"is_key\": 0, \"row_id\": 2179912, \"text\": \"Free\"}, {\"quad\": {\"x2\": 414, \"y3\": 886, \"x3\": 414, \"y4\": 886, \"x1\": 374, \"y1\": 864, \"x4\": 374, \"y2\": 864}, \"is_key\": 0, \"row_id\": 2179912, \"text\": \"Ice\"}, {\"quad\": {\"x2\": 464, \"y3\": 884, \"x3\": 464, \"y4\": 884, \"x1\": 422, \"y1\": 862, \"x4\": 422, \"y2\": 862}, \"is_key\": 0, \"row_id\": 2179912, \"text\": \"Tea\"}], \"category\": \"menu.nm\", \"group_id\": 22, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 640, \"y3\": 878, \"x3\": 640, \"y4\": 878, \"x1\": 622, \"y1\": 856, \"x4\": 622, \"y2\": 856}, \"is_key\": 0, \"row_id\": 2179912, \"text\": \"0\"}], \"category\": \"menu.price\", \"group_id\": 22, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 250, \"y3\": 920, \"x3\": 250, \"y4\": 920, \"x1\": 236, \"y1\": 900, \"x4\": 236, \"y2\": 900}, \"is_key\": 0, \"row_id\": 2179913, \"text\": \"1\"}, {\"quad\": {\"x2\": 276, \"y3\": 920, \"x3\": 276, \"y4\": 920, \"x1\": 260, \"y1\": 902, \"x4\": 260, \"y2\": 902}, \"is_key\": 0, \"row_id\": 2179913, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 23, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 376, \"y3\": 916, \"x3\": 376, \"y4\": 916, \"x1\": 308, \"y1\": 892, \"x4\": 308, \"y2\": 892}, \"is_key\": 0, \"row_id\": 2179913, \"text\": \"Bebek\"}, {\"quad\": {\"x2\": 464, \"y3\": 914, \"x3\": 464, \"y4\": 914, \"x1\": 384, \"y1\": 890, \"x4\": 384, \"y2\": 890}, \"is_key\": 0, \"row_id\": 2179913, \"text\": \"Street\"}], \"category\": \"menu.nm\", \"group_id\": 23, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 641, \"y3\": 908, \"x3\": 642, \"y4\": 911, \"x1\": 559, \"y1\": 884, \"x4\": 560, \"y2\": 881}, \"is_key\": 0, \"row_id\": 2179913, \"text\": \"44,000\"}], \"category\": \"menu.price\", \"group_id\": 23, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 250, \"y3\": 948, \"x3\": 250, \"y4\": 948, \"x1\": 238, \"y1\": 930, \"x4\": 238, \"y2\": 930}, \"is_key\": 0, \"row_id\": 2179914, \"text\": \"1\"}, {\"quad\": {\"x2\": 276, \"y3\": 946, \"x3\": 276, \"y4\": 946, \"x1\": 260, \"y1\": 930, \"x4\": 260, \"y2\": 930}, \"is_key\": 0, \"row_id\": 2179914, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 24, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 352, \"y3\": 946, \"x3\": 352, \"y4\": 946, \"x1\": 312, \"y1\": 924, \"x4\": 312, \"y2\": 924}, \"is_key\": 0, \"row_id\": 2179914, \"text\": \"Ice\"}, {\"quad\": {\"x2\": 402, \"y3\": 944, \"x3\": 402, \"y4\": 944, \"x1\": 360, \"y1\": 922, \"x4\": 360, \"y2\": 922}, \"is_key\": 0, \"row_id\": 2179914, \"text\": \"Tea\"}, {\"quad\": {\"x2\": 480, \"y3\": 942, \"x3\": 480, \"y4\": 942, \"x1\": 412, \"y1\": 920, \"x4\": 412, \"y2\": 920}, \"is_key\": 0, \"row_id\": 2179914, \"text\": \"Tawar\"}], \"category\": \"menu.nm\", \"group_id\": 24, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 642, \"y3\": 938, \"x3\": 642, \"y4\": 938, \"x1\": 564, \"y1\": 912, \"x4\": 564, \"y2\": 912}, \"is_key\": 0, \"row_id\": 2179914, \"text\": \"18,000\"}], \"category\": \"menu.price\", \"group_id\": 24, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 479, \"y3\": 998, \"x3\": 481, \"y4\": 1005, \"x1\": 360, \"y1\": 979, \"x4\": 362, \"y2\": 973}, \"is_key\": 1, \"row_id\": 2179915, \"text\": \"Sub-Total\"}, {\"quad\": {\"x2\": 645, \"y3\": 995, \"x3\": 646, \"y4\": 998, \"x1\": 527, \"y1\": 970, \"x4\": 528, \"y2\": 967}, \"is_key\": 0, \"row_id\": 2179915, \"text\": \"1,346,000\"}], \"category\": \"sub_total.subtotal_price\", \"group_id\": 25, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 481, \"y3\": 1027, \"x3\": 482, \"y4\": 1030, \"x1\": 387, \"y1\": 1007, \"x4\": 388, \"y2\": 1004}, \"is_key\": 1, \"row_id\": 2179916, \"text\": \"Service\"}, {\"quad\": {\"x2\": 646, \"y3\": 1026, \"x3\": 646, \"y4\": 1026, \"x1\": 554, \"y1\": 998, \"x4\": 554, \"y2\": 998}, \"is_key\": 0, \"row_id\": 2179916, \"text\": \"100,950\"}], \"category\": \"sub_total.service_price\", \"group_id\": 25, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 482, \"y3\": 1056, \"x3\": 482, \"y4\": 1056, \"x1\": 438, \"y1\": 1032, \"x4\": 438, \"y2\": 1032}, \"is_key\": 1, \"row_id\": 2179917, \"text\": \"PB1\"}, {\"quad\": {\"x2\": 648, \"y3\": 1052, \"x3\": 648, \"y4\": 1052, \"x1\": 556, \"y1\": 1026, \"x4\": 556, \"y2\": 1026}, \"is_key\": 0, \"row_id\": 2179917, \"text\": \"144,695\"}], \"category\": \"sub_total.tax_price\", \"group_id\": 25, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 481, \"y3\": 1085, \"x3\": 482, \"y4\": 1088, \"x1\": 375, \"y1\": 1063, \"x4\": 376, \"y2\": 1061}, \"is_key\": 1, \"row_id\": 2179918, \"text\": \"Rounding\"}, {\"quad\": {\"x2\": 648, \"y3\": 1078, \"x3\": 648, \"y4\": 1078, \"x1\": 606, \"y1\": 1054, \"x4\": 606, \"y2\": 1054}, \"is_key\": 0, \"row_id\": 2179918, \"text\": \"-45\"}], \"category\": \"sub_total.etc\", \"group_id\": 25, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 334, \"y3\": 1162, \"x3\": 334, \"y4\": 1162, \"x1\": 266, \"y1\": 1142, \"x4\": 266, \"y2\": 1142}, \"is_key\": 1, \"row_id\": 2179919, \"text\": \"Grand\"}, {\"quad\": {\"x2\": 408, \"y3\": 1160, \"x3\": 408, \"y4\": 1160, \"x1\": 340, \"y1\": 1138, \"x4\": 340, \"y2\": 1138}, \"is_key\": 1, \"row_id\": 2179919, \"text\": \"Total\"}, {\"quad\": {\"x2\": 647, \"y3\": 1153, \"x3\": 649, \"y4\": 1161, \"x1\": 418, \"y1\": 1117, \"x4\": 420, \"y2\": 1108}, \"is_key\": 0, \"row_id\": 2179919, \"text\": \"1,591,600\"}], \"category\": \"total.total_price\", \"group_id\": 26, \"sub_group_id\": 0}], \"roi\": {}, \"repeating_symbol\": [], \"dontcare\": []}'"
            ]
          },
          "execution_count": 6,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "example[\"ground_truth\"]"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0ZPE8Yhf89qp"
      },
      "source": [
        "Cool! So this contains a ground truth parsing that we want the model to output given an image. We can read it as json:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "_67bDART89qq",
        "outputId": "0eb2b54c-f5aa-4829-c42c-e2b0bcff9989"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "{'menu': [{'nm': 'Nasi Campur Bali', 'cnt': '1 x', 'price': '75,000'}, {'nm': 'Bbk Bengil Nasi', 'cnt': '1 x', 'price': '125,000'}, {'nm': 'MilkShake Starwb', 'cnt': '1 x', 'price': '37,000'}, {'nm': 'Ice Lemon Tea', 'cnt': '1 x', 'price': '24,000'}, {'nm': 'Nasi Ayam Dewata', 'cnt': '1 x', 'price': '70,000'}, {'nm': 'Free Ice Tea', 'cnt': '3 x', 'price': '0'}, {'nm': 'Organic Green Sa', 'cnt': '1 x', 'price': '65,000'}, {'nm': 'Ice Tea', 'cnt': '1 x', 'price': '18,000'}, {'nm': 'Ice Orange', 'cnt': '1 x', 'price': '29,000'}, {'nm': 'Ayam Suir Bali', 'cnt': '1 x', 'price': '85,000'}, {'nm': 'Tahu Goreng', 'cnt': '2 x', 'price': '36,000'}, {'nm': 'Tempe Goreng', 'cnt': '2 x', 'price': '36,000'}, {'nm': 'Tahu Telor Asin', 'cnt': '1 x', 'price': '40,000.'}, {'nm': 'Nasi Goreng Samb', 'cnt': '1 x', 'price': '70,000'}, {'nm': 'Bbk Panggang Sam', 'cnt': '3 x', 'price': '366,000'}, {'nm': 'Ayam Sambal Hija', 'cnt': '1 x', 'price': '92,000'}, {'nm': 'Hot Tea', 'cnt': '2 x', 'price': '44,000'}, {'nm': 'Ice Kopi', 'cnt': '1 x', 'price': '32,000'}, {'nm': 'Tahu Telor Asin', 'cnt': '1 x', 'price': '40,000'}, {'nm': 'Free Ice Tea', 'cnt': '1 x', 'price': '0'}, {'nm': 'Bebek Street', 'cnt': '1 x', 'price': '44,000'}, {'nm': 'Ice Tea Tawar', 'cnt': '1 x', 'price': '18,000'}], 'sub_total': {'subtotal_price': '1,346,000', 'service_price': '100,950', 'tax_price': '144,695', 'etc': '-45'}, 'total': {'total_price': '1,591,600'}}\n"
          ]
        }
      ],
      "source": [
        "import json\n",
        "\n",
        "ground_truth_json = json.loads(example[\"ground_truth\"])\n",
        "\n",
        "print(ground_truth_json[\"gt_parse\"])"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rc_ECuu689qq"
      },
      "source": [
        "## Load processor\n",
        "\n",
        "Next, we'll load the processor which is used to prepare the data in the format that the model expects. Neural networks like LLaVa don't directly take images and text as input, but rather `pixel_values` (which is a resized, rescaled, normalized and optionally splitted version of the receipt images), `input_ids` (which are text token indices in the vocabulary of the model), etc. This is handled by the processor.\n",
        "\n",
        "### Image resolution\n",
        "\n",
        "The image resolution at which multimodal models are trained greatly has an impact on performance. One of the shortcomings of LLaVa is that it uses a fairly low image resolution (336x336). Newer models like LLaVa-NeXT and Idefics2 use a much higher image resolution enabling the model to \"see\" a lot more details in the image (which improves its OCR performance among other things). On the other hand, using a bigger image resolution comes at a cost of much higher memory requirements and longer training times. This is less of an issue with LLaVa due to its relatively small image resolution."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "6XW3qVty89qq",
        "outputId": "c8ec0f67-0f56-4f16-f3f9-7af975d0904b"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "2024-05-12 10:04:20.152405: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
            "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
            "2024-05-12 10:04:20.895890: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n",
            "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n"
          ]
        }
      ],
      "source": [
        "from transformers import AutoProcessor\n",
        "\n",
        "processor = AutoProcessor.from_pretrained(MODEL_ID)\n",
        "processor.tokenizer.padding_side = \"right\" # during training, one always uses padding on the right"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yHhDJ8Fs89qq"
      },
      "source": [
        "## Load model\n",
        "\n",
        "Next, we're going to load the LLaVa model from the [hub](https://huggingface.co/llava-hf/llava-1.5-7b-hf). This is a model with about 7 billion trainable parameters (as it combines a LLaMa-7B language model with a relatively low-parameter vision encoder). Do note that we load a model here which already has undergone supervised fine-tuning (SFT) on the [LLaVa-Instruct-150K](https://huggingface.co/datasets/liuhaotian/LLaVA-Instruct-150K) instruction dataset. We can benefit from the fine-tuning that the model already has undergone.\n",
        "\n",
        "### Full fine-tuning, LoRa and Q-LoRa\n",
        "\n",
        "As this model has 7 billion trainable parameters, that's going to have quite an impact on the amount of memory used. For reference, fine-tuning a model using the [AdamW optimizer](https://pytorch.org/docs/stable/generated/torch.optim.AdamW.html#torch.optim.AdamW) (which is often used to optimize neural networks) with mixed precision, you need about 18 times the amount of parameters in GB of GPU RAM. So in this case, we would need 18x7 billion bytes = 126 GB of GPU RAM if we want to update all the parameters of the model!! That's huge right? And for most people infeasible.\n",
        "\n",
        "Luckily, some clever people came up with the [LoRa](https://huggingface.co/docs/peft/main/en/conceptual_guides/lora) method (LoRa is short for low-rank adapation). It allows to just freeze the existing weights and only train a couple of adapter layers on top of the base model. Hugging Face offers the separate [PEFT library](https://huggingface.co/docs/peft/main/en/index) for easy use of LoRa, along with other Parameter-Efficient Fine-Tuning methods (that's where the name PEFT comes from).\n",
        "\n",
        "Moreover, one can not only freeze the existing base model but also quantize it (which means, shrinking down its size). A neural network's parameters are typically saved in either float32 (which means, 32 bits or 4 bytes are used to store each parameter value) or float16 (which means, 16 bits or half a byte - also called half precision). However, with some clever algorithms one can shrink each parameter to just 8 or 4 bits (half a byte!), without significant effect on final performance. Read all about it here: https://huggingface.co/blog/4bit-transformers-bitsandbytes.\n",
        "\n",
        "This means that we're going to shrink the size of the base Idefics2-8b model considerably using 4-bit quantization, and then only train a couple of adapter layers on top using LoRa (in float16). This idea of combining LoRa with quantization is called Q-LoRa and is the most memory friendly version.\n",
        "\n",
        "Of course, if you have the memory available, feel free to use full fine-tuning or LoRa without quantization! In case of full fine-tuning, the code snippet below instantiates the model with Flash Attention which considerably speeds up computations.\n",
        "\n",
        "There exist many forms of quantization, here we leverage the [BitsAndBytes](https://huggingface.co/docs/transformers/main_classes/quantization#transformers.BitsAndBytesConfig) integration."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "PCbRwGgU89qq",
        "outputId": "f3dcec0e-6b03-407c-ecee-992259c39175"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/home/niels/python_projects/transformers/src/transformers/models/llava/configuration_llava.py:103: FutureWarning: The `vocab_size` argument is deprecated and will be removed in v4.42, since it can be inferred from the `text_config`. Passing this argument has no effect\n",
            "  warnings.warn(\n",
            "`low_cpu_mem_usage` was None, now set to True since model is quantized.\n",
            "Loading checkpoint shards: 100%|██████████| 3/3 [00:25<00:00,  8.60s/it]\n"
          ]
        }
      ],
      "source": [
        "from transformers import BitsAndBytesConfig, LlavaForConditionalGeneration\n",
        "import torch\n",
        "\n",
        "USE_LORA = False\n",
        "USE_QLORA = True\n",
        "\n",
        "## Load model\n",
        "\n",
        "# Three options for training, from the lowest precision training to the highest precision training:\n",
        "# - QLora\n",
        "# - Standard Lora\n",
        "# - Full fine-tuning\n",
        "if USE_QLORA or USE_LORA:\n",
        "    if USE_QLORA:\n",
        "        bnb_config = BitsAndBytesConfig(\n",
        "            load_in_4bit=True, bnb_4bit_quant_type=\"nf4\", bnb_4bit_compute_dtype=torch.float16\n",
        "        )\n",
        "    model = LlavaForConditionalGeneration.from_pretrained(\n",
        "        MODEL_ID,\n",
        "        torch_dtype=torch.float16,\n",
        "        quantization_config=bnb_config,\n",
        "    )\n",
        "else:\n",
        "    # for full fine-tuning, we can speed up the model using Flash Attention\n",
        "    # only available on certain devices, see https://github.com/Dao-AILab/flash-attention?tab=readme-ov-file#installation-and-features\n",
        "    model = LlavaForConditionalGeneration.from_pretrained(\n",
        "        MODEL_ID,\n",
        "        torch_dtype=torch.float16,\n",
        "        _attn_implementation=\"flash_attention_2\",\n",
        "    )"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8P6BtgGz89qq"
      },
      "source": [
        "## Apply PEFT\n",
        "\n",
        "After loading the base model, we're going to add LoRa adapter layers. We're going to only train these adapter layers (the base model is kept frozen).\n",
        "\n",
        "The difference here with other models are the layers at which we're going to add adapters (in PEFT this is called `target_modules`). This typically depends a bit on the model.\n",
        "\n",
        "Here, I based myself off the original `find_all_linear_names` [function](https://github.com/haotian-liu/LLaVA/blob/ec3a32ddea47d8739cb6523fb2661b635c15827e/llava/train/train.py#L169) found in the original LLaVa repository. It means that we're going to add adapters to all linear layers of the model (`nn.Linear`), except for the ones present in the vision encoder and multimodal projector. This means that we're mostly going to adapt the language model part of LLaVa for our use case."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "vHMXc9Xb89qq"
      },
      "outputs": [],
      "source": [
        "from peft import LoraConfig, prepare_model_for_kbit_training, get_peft_model\n",
        "\n",
        "\n",
        "def find_all_linear_names(model):\n",
        "    cls = torch.nn.Linear\n",
        "    lora_module_names = set()\n",
        "    multimodal_keywords = ['multi_modal_projector', 'vision_model']\n",
        "    for name, module in model.named_modules():\n",
        "        if any(mm_keyword in name for mm_keyword in multimodal_keywords):\n",
        "            continue\n",
        "        if isinstance(module, cls):\n",
        "            names = name.split('.')\n",
        "            lora_module_names.add(names[0] if len(names) == 1 else names[-1])\n",
        "\n",
        "    if 'lm_head' in lora_module_names: # needed for 16-bit\n",
        "        lora_module_names.remove('lm_head')\n",
        "    return list(lora_module_names)\n",
        "\n",
        "\n",
        "lora_config = LoraConfig(\n",
        "    r=8,\n",
        "    lora_alpha=8,\n",
        "    lora_dropout=0.1,\n",
        "    target_modules=find_all_linear_names(model),\n",
        "    init_lora_weights=\"gaussian\",\n",
        ")\n",
        "\n",
        "model = prepare_model_for_kbit_training(model)\n",
        "model = get_peft_model(model, lora_config)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "64gK5tEB89qq"
      },
      "source": [
        "## Create PyTorch dataset\n",
        "\n",
        "Next we'll create a regular [PyTorch dataset](https://pytorch.org/tutorials/beginner/basics/data_tutorial.html) which defines the individual items of the dataset. For that, one needs to implement 3 methods: an `init` method, a `len` method (which returns the length of the dataset) and a `getitem` method (which returns items of the dataset).\n",
        "\n",
        "The `init` method goes over all the ground truth JSON sequences and turns them into token sequences (which we want the model to generate) using the `json2token` method. Unlike in my Donut and Idefics2 notebooks, we're not going to add special tokens to the model's vocabulary to omit complexity. Feel free to check them out, I haven't ablated whether adding special tokens gives a big boost in performance.\n",
        "\n",
        "Typically, one uses the processor in the `getitem` method to prepare the data in the format that the model expects, but we'll postpone that here for a reason we'll explain later. In our case we're just going to return 2 things: the image and a corresponding ground truth token sequence."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "jHNidtY689qq"
      },
      "outputs": [],
      "source": [
        "from torch.utils.data import Dataset\n",
        "from typing import Any, Dict\n",
        "import random\n",
        "\n",
        "class LlavaDataset(Dataset):\n",
        "    \"\"\"\n",
        "    PyTorch Dataset for LLaVa. This class takes a HuggingFace Dataset as input.\n",
        "\n",
        "    Each row, consists of image path(png/jpg/jpeg) and ground truth data (json/jsonl/txt).\n",
        "    \"\"\"\n",
        "\n",
        "    def __init__(\n",
        "        self,\n",
        "        dataset_name_or_path: str,\n",
        "        split: str = \"train\",\n",
        "        sort_json_key: bool = True,\n",
        "    ):\n",
        "        super().__init__()\n",
        "\n",
        "        self.split = split\n",
        "        self.sort_json_key = sort_json_key\n",
        "\n",
        "        self.dataset = load_dataset(dataset_name_or_path, split=self.split)\n",
        "        self.dataset_length = len(self.dataset)\n",
        "\n",
        "        self.gt_token_sequences = []\n",
        "        for sample in self.dataset:\n",
        "            ground_truth = json.loads(sample[\"ground_truth\"])\n",
        "            if \"gt_parses\" in ground_truth:  # when multiple ground truths are available, e.g., docvqa\n",
        "                assert isinstance(ground_truth[\"gt_parses\"], list)\n",
        "                gt_jsons = ground_truth[\"gt_parses\"]\n",
        "            else:\n",
        "                assert \"gt_parse\" in ground_truth and isinstance(ground_truth[\"gt_parse\"], dict)\n",
        "                gt_jsons = [ground_truth[\"gt_parse\"]]\n",
        "\n",
        "            self.gt_token_sequences.append(\n",
        "                [\n",
        "                    self.json2token(\n",
        "                        gt_json,\n",
        "                        sort_json_key=self.sort_json_key,\n",
        "                    )\n",
        "                    for gt_json in gt_jsons  # load json from list of json\n",
        "                ]\n",
        "            )\n",
        "\n",
        "    def json2token(self, obj: Any, sort_json_key: bool = True):\n",
        "        \"\"\"\n",
        "        Convert an ordered JSON object into a token sequence\n",
        "        \"\"\"\n",
        "        if type(obj) == dict:\n",
        "            if len(obj) == 1 and \"text_sequence\" in obj:\n",
        "                return obj[\"text_sequence\"]\n",
        "            else:\n",
        "                output = \"\"\n",
        "                if sort_json_key:\n",
        "                    keys = sorted(obj.keys(), reverse=True)\n",
        "                else:\n",
        "                    keys = obj.keys()\n",
        "                for k in keys:\n",
        "                    output += (\n",
        "                        fr\"<s_{k}>\"\n",
        "                        + self.json2token(obj[k], sort_json_key)\n",
        "                        + fr\"</s_{k}>\"\n",
        "                    )\n",
        "                return output\n",
        "        elif type(obj) == list:\n",
        "            return r\"<sep/>\".join(\n",
        "                [self.json2token(item, sort_json_key) for item in obj]\n",
        "            )\n",
        "        else:\n",
        "            obj = str(obj)\n",
        "            return obj\n",
        "\n",
        "    def __len__(self) -> int:\n",
        "        return self.dataset_length\n",
        "\n",
        "    def __getitem__(self, idx: int) -> Dict:\n",
        "        \"\"\"\n",
        "        Returns one item of the dataset.\n",
        "\n",
        "        Returns:\n",
        "            image : the original Receipt image\n",
        "            target_sequence : tokenized ground truth sequence\n",
        "        \"\"\"\n",
        "        sample = self.dataset[idx]\n",
        "\n",
        "        # inputs\n",
        "        image = sample[\"image\"]\n",
        "        target_sequence = random.choice(self.gt_token_sequences[idx])  # can be more than one, e.g., DocVQA Task 1\n",
        "\n",
        "        return image, target_sequence"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MmEj8Xjx89qr"
      },
      "source": [
        "Let's instantiate the PyTorch datasets:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "VG-74l9189qr"
      },
      "outputs": [],
      "source": [
        "train_dataset = LlavaDataset(\"naver-clova-ix/cord-v2\",  split=\"train\", sort_json_key=False)\n",
        "val_dataset = LlavaDataset(\"naver-clova-ix/cord-v2\", split=\"validation\", sort_json_key=False)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CNm0Ui1a89qr"
      },
      "source": [
        "As always, it's important to check your data. Let's check the first example:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "S1AiW6oa89qr",
        "outputId": "3efff66a-a781-4572-f45d-ee9d7d2a806c"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "<s_menu><s_nm>Nasi Campur Bali</s_nm><s_cnt>1 x</s_cnt><s_price>75,000</s_price><sep/><s_nm>Bbk Bengil Nasi</s_nm><s_cnt>1 x</s_cnt><s_price>125,000</s_price><sep/><s_nm>MilkShake Starwb</s_nm><s_cnt>1 x</s_cnt><s_price>37,000</s_price><sep/><s_nm>Ice Lemon Tea</s_nm><s_cnt>1 x</s_cnt><s_price>24,000</s_price><sep/><s_nm>Nasi Ayam Dewata</s_nm><s_cnt>1 x</s_cnt><s_price>70,000</s_price><sep/><s_nm>Free Ice Tea</s_nm><s_cnt>3 x</s_cnt><s_price>0</s_price><sep/><s_nm>Organic Green Sa</s_nm><s_cnt>1 x</s_cnt><s_price>65,000</s_price><sep/><s_nm>Ice Tea</s_nm><s_cnt>1 x</s_cnt><s_price>18,000</s_price><sep/><s_nm>Ice Orange</s_nm><s_cnt>1 x</s_cnt><s_price>29,000</s_price><sep/><s_nm>Ayam Suir Bali</s_nm><s_cnt>1 x</s_cnt><s_price>85,000</s_price><sep/><s_nm>Tahu Goreng</s_nm><s_cnt>2 x</s_cnt><s_price>36,000</s_price><sep/><s_nm>Tempe Goreng</s_nm><s_cnt>2 x</s_cnt><s_price>36,000</s_price><sep/><s_nm>Tahu Telor Asin</s_nm><s_cnt>1 x</s_cnt><s_price>40,000.</s_price><sep/><s_nm>Nasi Goreng Samb</s_nm><s_cnt>1 x</s_cnt><s_price>70,000</s_price><sep/><s_nm>Bbk Panggang Sam</s_nm><s_cnt>3 x</s_cnt><s_price>366,000</s_price><sep/><s_nm>Ayam Sambal Hija</s_nm><s_cnt>1 x</s_cnt><s_price>92,000</s_price><sep/><s_nm>Hot Tea</s_nm><s_cnt>2 x</s_cnt><s_price>44,000</s_price><sep/><s_nm>Ice Kopi</s_nm><s_cnt>1 x</s_cnt><s_price>32,000</s_price><sep/><s_nm>Tahu Telor Asin</s_nm><s_cnt>1 x</s_cnt><s_price>40,000</s_price><sep/><s_nm>Free Ice Tea</s_nm><s_cnt>1 x</s_cnt><s_price>0</s_price><sep/><s_nm>Bebek Street</s_nm><s_cnt>1 x</s_cnt><s_price>44,000</s_price><sep/><s_nm>Ice Tea Tawar</s_nm><s_cnt>1 x</s_cnt><s_price>18,000</s_price></s_menu><s_sub_total><s_subtotal_price>1,346,000</s_subtotal_price><s_service_price>100,950</s_service_price><s_tax_price>144,695</s_tax_price><s_etc>-45</s_etc></s_sub_total><s_total><s_total_price>1,591,600</s_total_price></s_total>\n"
          ]
        }
      ],
      "source": [
        "train_example = train_dataset[0]\n",
        "image, target_sequence = train_example\n",
        "print(target_sequence)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WLChlej489qr"
      },
      "source": [
        "## Define collate functions\n",
        "\n",
        "Now that we have PyTorch datasets, we'll define a so-called collators which define how items of the dataset should be batched together. This is because we typically train neural networks on batches of data (i.e. various images/target sequences combined) rather than one-by-one, using a variant of stochastic-gradient descent or SGD (like Adam, AdamW, etc.).\n",
        "\n",
        "It's only here that we're going to use the processor to turn the (image, target token sequence) into the format that the model expects (which is `pixel_values`, `input_ids` etc.). The reason we do that here is because it allows for **dynamic padding** of the batches: each batch contains ground truth sequences of varying lengths. By only using the processor here, we will pad the `input_ids` up to the largest sequence in the batch.\n",
        "\n",
        "We also decide to limit the length of the text tokens (`input_ids`) to a max length due to memory constraints, feel free to expand if your target token sequences are longer (I'd recommend plotting the average token length of your dataset to determine the optimal value).\n",
        "\n",
        "The formatting of the `input_ids` is super important: we need to respect a so-called [chat template](https://huggingface.co/docs/transformers/main/en/chat_templating). As of now, LLaVa does not yet support chat templates, so we manually write down the prompt in the correct format (which starts with USER and ends with ASSISTANT). I'll update my notebook when it is supported. We use the text prompt \"Extract JSON\", this is just a deliberate choice, you could also omit this and just train the model on (image, JSON) pairs without text prompt.\n",
        "\n",
        "Labels are created for the model by simply copying the inputs to the LLM (`input_ids`), but with padding tokens replaced by the ignore index of the loss function. This ensures that the model doesn't need to learn to predict padding tokens (used to batch examples together).\n",
        "\n",
        "Why are the labels a copy of the model inputs, you may ask? The model will internally shift the labels one position to the right so that the model will learn to predict the next token. This can be seen [here](https://github.com/huggingface/transformers/blob/6f465d45d98f9eaeef83cfdfe79aecc7193b0f1f/src/transformers/models/idefics2/modeling_idefics2.py#L1851-L1855).\n",
        "\n",
        "The collate function for evaluation is different, since there we only need to feed the prompt to the model, as we'll use the `generate()` method to autoregressively generate a completion."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "NFxVN7OK89qr"
      },
      "outputs": [],
      "source": [
        "def train_collate_fn(examples):\n",
        "    images = []\n",
        "    texts = []\n",
        "    for example in examples:\n",
        "        image, ground_truth = example\n",
        "        images.append(image)\n",
        "        # TODO: in the future we can replace this by processor.apply_chat_template\n",
        "        prompt = f\"USER: <image>\\nExtract JSON.\\nASSISTANT: {ground_truth}\"\n",
        "        texts.append(prompt)\n",
        "\n",
        "    batch = processor(text=texts, images=images, padding=True, truncation=True, max_length=MAX_LENGTH, return_tensors=\"pt\")\n",
        "\n",
        "    labels = batch[\"input_ids\"].clone()\n",
        "    labels[labels == processor.tokenizer.pad_token_id] = -100\n",
        "    batch[\"labels\"] = labels\n",
        "\n",
        "    input_ids = batch[\"input_ids\"]\n",
        "    attention_mask = batch[\"attention_mask\"]\n",
        "    pixel_values = batch[\"pixel_values\"]\n",
        "    labels = batch[\"labels\"]\n",
        "\n",
        "    return input_ids, attention_mask, pixel_values, labels\n",
        "\n",
        "\n",
        "def eval_collate_fn(examples):\n",
        "    # we only feed the prompt to the model\n",
        "    images = []\n",
        "    texts = []\n",
        "    answers = []\n",
        "    for example in examples:\n",
        "        image, ground_truth = example\n",
        "        images.append(image)\n",
        "        # TODO: in the future we can replace this by processor.apply_chat_template\n",
        "        prompt = f\"USER: <image>\\nExtract JSON.\\nASSISTANT:\"\n",
        "        texts.append(prompt)\n",
        "        answers.append(ground_truth)\n",
        "\n",
        "    batch = processor(text=texts, images=images, return_tensors=\"pt\", padding=True)\n",
        "\n",
        "    input_ids = batch[\"input_ids\"]\n",
        "    attention_mask = batch[\"attention_mask\"]\n",
        "    pixel_values = batch[\"pixel_values\"]\n",
        "\n",
        "    return input_ids, attention_mask, pixel_values, answers"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BCKx3T0I89qr"
      },
      "source": [
        "## Define PyTorch LightningModule\n",
        "\n",
        "There are various ways to train a PyTorch model: one could just use native PyTorch, use the [Trainer API](https://huggingface.co/docs/transformers/en/main_classes/trainer) or frameworks like [Accelerate](https://huggingface.co/docs/accelerate/en/index). In this notebook, I'll use PyTorch Lightning as it allows to easily compute evaluation metrics during training.\n",
        "\n",
        "Below, we define a [LightningModule](https://lightning.ai/docs/pytorch/stable/common/lightning_module.html), which is the standard way to train a model in PyTorch Lightning. A LightningModule is an `nn.Module` with some additional functionality.\n",
        "\n",
        "Basically, PyTorch Lightning will take care of all device placements (`.to(device)`) for us, as well as the backward pass, putting the model in training mode, etc.\n",
        "\n",
        "Notice the difference between a training step and an evaluation step:\n",
        "\n",
        "- a training step only consists of a forward pass, in which we compute the cross-entropy loss between the model's next token predictions and the ground truth (in parallel for all tokens, this technique is known as \"teacher forcing\"). The backward pass is handled by PyTorch Lightning.\n",
        "- an evaluation step consists of making the model autoregressively complete the prompt using the [`generate()`](https://huggingface.co/docs/transformers/v4.40.1/en/main_classes/text_generation#transformers.GenerationMixin.generate) method. After that, we compute an evaluation metric between the predicted sequences and the ground truth ones. This allows us to see how the model is improving over the course of training. The metric we use here is the so-called [Levenhstein edit distance](https://en.wikipedia.org/wiki/Levenshtein_distance). This quantifies how much we would need to edit the predicted token sequence to get the target sequence (the fewer edits the better!). Its optimal value is 0 (which means, no edits need to be made).\n",
        "\n",
        "Besides that, we define the optimizer to use ([AdamW](https://pytorch.org/docs/stable/generated/torch.optim.AdamW.html) is a good default choice) and the data loaders, which use the collate functions defined above to batch together items of the PyTorch datasets. Do note that AdamW is a pretty heavy optimizer in terms of memory requirements, but as we're training with QLoRa we only need to store optimizer states for the adapter layers. For full fine-tuning, one could take a look at more memory friendly optimizers such as [8-bit Adam](https://huggingface.co/docs/bitsandbytes/main/en/optimizers)."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "B0vMexZs89qr"
      },
      "outputs": [],
      "source": [
        "import lightning as L\n",
        "from torch.utils.data import DataLoader\n",
        "import re\n",
        "from nltk import edit_distance\n",
        "import numpy as np\n",
        "\n",
        "\n",
        "class LlavaModelPLModule(L.LightningModule):\n",
        "    def __init__(self, config, processor, model):\n",
        "        super().__init__()\n",
        "        self.config = config\n",
        "        self.processor = processor\n",
        "        self.model = model\n",
        "\n",
        "        self.batch_size = config.get(\"batch_size\")\n",
        "\n",
        "    def training_step(self, batch, batch_idx):\n",
        "\n",
        "        input_ids, attention_mask, pixel_values, labels = batch\n",
        "\n",
        "        outputs = self.model(input_ids=input_ids,\n",
        "                                attention_mask=attention_mask,\n",
        "                                pixel_values=pixel_values,\n",
        "                                labels=labels)\n",
        "        loss = outputs.loss\n",
        "\n",
        "        self.log(\"train_loss\", loss)\n",
        "\n",
        "        return loss\n",
        "\n",
        "    def validation_step(self, batch, batch_idx, dataset_idx=0):\n",
        "\n",
        "        input_ids, attention_mask, pixel_values, answers = batch\n",
        "\n",
        "        # autoregressively generate token IDs\n",
        "        generated_ids = self.model.generate(input_ids=input_ids, attention_mask=attention_mask,\n",
        "                                       pixel_values=pixel_values, max_new_tokens=MAX_LENGTH)\n",
        "        # turn them back into text, chopping of the prompt\n",
        "        # important: we don't skip special tokens here, because we want to see them in the output\n",
        "        predictions = self.processor.batch_decode(generated_ids[:, input_ids.size(1):], skip_special_tokens=True)\n",
        "\n",
        "        scores = []\n",
        "        for pred, answer in zip(predictions, answers):\n",
        "            pred = re.sub(r\"(?:(?<=>) | (?=</s_))\", \"\", pred)\n",
        "            scores.append(edit_distance(pred, answer) / max(len(pred), len(answer)))\n",
        "\n",
        "            if self.config.get(\"verbose\", False) and len(scores) == 1:\n",
        "                print(f\"Prediction: {pred}\")\n",
        "                print(f\"    Answer: {answer}\")\n",
        "                print(f\" Normed ED: {scores[0]}\")\n",
        "\n",
        "        self.log(\"val_edit_distance\", np.mean(scores))\n",
        "\n",
        "        return scores\n",
        "\n",
        "    def configure_optimizers(self):\n",
        "        # you could also add a learning rate scheduler if you want\n",
        "        optimizer = torch.optim.AdamW(self.parameters(), lr=self.config.get(\"lr\"))\n",
        "\n",
        "        return optimizer\n",
        "\n",
        "    def train_dataloader(self):\n",
        "        return DataLoader(train_dataset, collate_fn=train_collate_fn, batch_size=self.batch_size, shuffle=True, num_workers=4)\n",
        "\n",
        "    def val_dataloader(self):\n",
        "        return DataLoader(val_dataset, collate_fn=eval_collate_fn, batch_size=self.batch_size, shuffle=False, num_workers=4)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Ke22hzKm89qr"
      },
      "source": [
        "Let's instantiate it (based on a config dictionary which defines all hyperparameters for training).\n",
        "\n",
        "The batch size was determined based on PyTorch Lightning's [auto batch size finder](https://lightning.ai/docs/pytorch/stable/advanced/training_tricks.html#batch-size-finder) feature. It tries to find the biggest batch size for your given hardware.\n",
        "\n",
        "Do note that one can play around with the hyperparameters, I just use good defaults here: 10 epochs, a learning rate of 1e-4 which I found in the original Idefics2 notebook (linked at the top of this notebook), use mixed precision for training (more memory friendly). One could extend this with things like gradient accumulation and gradient checkpointing.\n",
        "\n",
        "I recommend [this guide](https://huggingface.co/docs/transformers/v4.20.1/en/perf_train_gpu_one) which goes over all tips and tricks regarding maximizing fine-tuning performance on consumer hardware."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "hOBWa7lt89qr"
      },
      "outputs": [],
      "source": [
        "config = {\"max_epochs\": 10,\n",
        "          # \"val_check_interval\": 0.2, # how many times we want to validate during an epoch\n",
        "          \"check_val_every_n_epoch\": 1,\n",
        "          \"gradient_clip_val\": 1.0,\n",
        "          \"accumulate_grad_batches\": 8,\n",
        "          \"lr\": 1e-4,\n",
        "          \"batch_size\": 2,\n",
        "          # \"seed\":2022,\n",
        "          \"num_nodes\": 1,\n",
        "          \"warmup_steps\": 50,\n",
        "          \"result_path\": \"./result\",\n",
        "          \"verbose\": True,\n",
        "}\n",
        "\n",
        "model_module = LlavaModelPLModule(config, processor, model)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TAENA-Rx89qr"
      },
      "source": [
        "## Define callbacks\n",
        "\n",
        "Optionally, Lightning allows to define so-called [callbacks](https://lightning.ai/docs/pytorch/stable/extensions/callbacks.html), which are arbitrary pieces of code that can be executed during training.\n",
        "\n",
        "Here I'm adding a `PushToHubCallback` which will push the model to the [hub](https://huggingface.co/) at the end of every epoch as well as at the end of training. Do note that you could of course also pass the `private=True` flag when pushing to the hub, if you wish to keep your model private. Hugging Face also offers the [Enterprise Hub](https://huggingface.co/enterprise) so that you can easily share models with your colleagues privately in a secure way.\n",
        "\n",
        "We'll also use the EarlyStopping callback of Lightning, which will automatically stop training once the evaluation metric (edit distance in our case) doesn't improve after 3 epochs."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "qpy69j-V89qs"
      },
      "outputs": [],
      "source": [
        "from lightning.pytorch.callbacks import Callback\n",
        "from lightning.pytorch.callbacks.early_stopping import EarlyStopping\n",
        "\n",
        "from huggingface_hub import HfApi\n",
        "\n",
        "api = HfApi()\n",
        "\n",
        "class PushToHubCallback(Callback):\n",
        "    def on_train_epoch_end(self, trainer, pl_module):\n",
        "        print(f\"Pushing model to the hub, epoch {trainer.current_epoch}\")\n",
        "        pl_module.model.push_to_hub(REPO_ID,\n",
        "                                    commit_message=f\"Training in progress, epoch {trainer.current_epoch}\")\n",
        "\n",
        "    def on_train_end(self, trainer, pl_module):\n",
        "        print(f\"Pushing model to the hub after training\")\n",
        "        pl_module.processor.push_to_hub(REPO_ID,\n",
        "                                    commit_message=f\"Training done\")\n",
        "        pl_module.model.push_to_hub(REPO_ID,\n",
        "                                    commit_message=f\"Training done\")\n",
        "\n",
        "early_stop_callback = EarlyStopping(monitor=\"val_edit_distance\", patience=3, verbose=False, mode=\"min\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SIr62vI-89qs"
      },
      "source": [
        "## Train!\n",
        "\n",
        "Alright, we're set to start training! We will also pass the Weights and Biases logger so that we get see some pretty plots of our loss and evaluation metric during training (do note that you may need to log in the first time you run this, see the [docs](https://docs.wandb.ai/guides/integrations/lightning)).\n",
        "\n",
        "Do note that this Trainer class supports many more flags! See the docs: https://lightning.ai/docs/pytorch/stable/api/lightning.pytorch.trainer.trainer.Trainer.html#lightning.pytorch.trainer.trainer.Trainer."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "OOvYRTRA89qs",
        "outputId": "ecd5a2aa-66b1-48ae-d13b-17d32d82b157"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "Using 16bit Automatic Mixed Precision (AMP)\n",
            "GPU available: True (cuda), used: True\n",
            "TPU available: False, using: 0 TPU cores\n",
            "IPU available: False, using: 0 IPUs\n",
            "HPU available: False, using: 0 HPUs\n",
            "/home/niels/python_projects/transformers/env/lib/python3.8/site-packages/lightning/pytorch/loggers/wandb.py:396: There is a wandb run already in progress and newly created instances of `WandbLogger` will reuse this run. If this is not desired, call `wandb.finish()` before instantiating `WandbLogger`.\n",
            "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [1]\n",
            "\n",
            "  | Name  | Type      | Params\n",
            "------------------------------------\n",
            "0 | model | PeftModel | 3.7 B \n",
            "------------------------------------\n",
            "21.2 M    Trainable params\n",
            "3.7 B     Non-trainable params\n",
            "3.7 B     Total params\n",
            "14,740.447Total estimated model params size (MB)\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Epoch 0: 100%|██████████| 400/400 [05:37<00:00,  1.19it/s, v_num=gio6]Prediction: <s_menu><s_nm>Real ganache</s_nm><s_cnt>1</s_cnt><s_price>16,500</s_price><sep/><s_nm>Egg tart</s_nm><s_cnt>1</s_cnt><s_price>13,000</s_price><sep/><s_nm>Pizza toast</s_nm><s_cnt>1</s_cnt><s_price>16,000</s_price></s_menu><s_total><s_total_price>45,500</s_total_price><s_cashprice>50,000</s_cashprice><s_changeprice>4,500</s_changeprice></s_total>\n",
            "    Answer: <s_menu><s_nm>REAL GANACHE</s_nm><s_cnt>1</s_cnt><s_price>16,500</s_price><sep/><s_nm>EGG TART</s_nm><s_cnt>1</s_cnt><s_price>13,000</s_price><sep/><s_nm>PIZZA TOAST</s_nm><s_cnt>1</s_cnt><s_price>16,000</s_price></s_menu><s_total><s_total_price>45,500</s_total_price><s_cashprice>50,000</s_cashprice><s_changeprice>4,500</s_changeprice></s_total>\n",
            " Normed ED: 0.07204610951008646\n",
            "Prediction: <s_menu><s_nm>S-Ovaltime</s_nm><s_cnt>1</s_cnt><s_price>20,000</s_price></s_menu><s_sub_total><s_subtotal_price>20,000</s_subtotal_price><s_tax_price>1,818</s_tax_price></s_sub_total><s_total><s_total_price>20,000</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>80,000</s_changeprice></s_total>\n",
            "    Answer: <s_menu><s_nm>S-Ovaltine 50%</s_nm><s_unitprice>20,000</s_unitprice><s_cnt>1</s_cnt><s_price>20,000</s_price><s_vatyn>10% Tax Included</s_vatyn></s_menu><s_sub_total><s_subtotal_price>18,181</s_subtotal_price><s_tax_price>1,818</s_tax_price></s_sub_total><s_total><s_total_price>20,000</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>80,000</s_changeprice></s_total>\n",
            " Normed ED: 0.20418848167539266\n",
            "Prediction: <s_menu><s_nm>BBQ Chicken</s_nm><s_cnt>1</s_cnt><s_price>41,000</s_price><s_sub><s_nm>- Sedang</s_nm><s_cnt>1</s_cnt><s_price>0</s_price></s_sub></s_menu><s_sub_total><s_subtotal_price>41,000</s_subtotal_price></s_sub_total><s_total><s_total_price>41,000</s_total_price><s_cashprice>50,000</s_cashprice><s_changeprice>9,000</s_changeprice></s_total>\n",
            "    Answer: <s_menu><s_nm>BBQ Chicken</s_nm><s_cnt>1</s_cnt><s_price>41,000</s_price><s_sub><s_nm>Sedang</s_nm><s_cnt>1</s_cnt><s_price>0</s_price></s_sub></s_menu><s_sub_total><s_subtotal_price>41,000</s_subtotal_price></s_sub_total><s_total><s_total_price>41,000</s_total_price><s_cashprice>50.000</s_cashprice><s_changeprice>:9,000</s_changeprice><s_menuqty_cnt>1</s_menuqty_cnt></s_total>\n",
            " Normed ED: 0.09473684210526316\n",
            "Prediction: <s_menu><s_nm>POTATO SAUSAGE BREAD</s_nm><s_cnt>1</s_cnt><s_price>19,000</s_price><sep/><s_nm>OREO GREEN TEA SPREAD</s_nm><s_cnt>1</s_cnt><s_price>19,000</s_price><sep/><s_nm>WHITE CHOCO BANANA SPREAD</s_nm><s_cnt>1</s_cnt><s_price>22,000</s_price></s_menu><s_total><s_total_price>123,000</s_total_price><s_creditcardprice>123,000</s_creditcardprice></s_total>\n",
            "    Answer: <s_menu><s_nm>POTATO SAUSAGE BREAD</s_nm><s_cnt>1</s_cnt><s_price>19,000</s_price><sep/><s_nm>OREO GREEN TEA SPREAD</s_nm><s_cnt>1</s_cnt><s_price>52,000</s_price><sep/><s_nm>WHITE CHOCO BANANA SPREAD</s_nm><s_cnt>1</s_cnt><s_price>52,000</s_price></s_menu><s_total><s_total_price>123,000</s_total_price><s_creditcardprice>123,000</s_creditcardprice></s_total>\n",
            " Normed ED: 0.008333333333333333\n",
            "Prediction: <s_menu><s_nm>TALAH UNGU</s_nm><s_discountprice>-40.000</s_discountprice><s_price>19,500</s_price><sep/><s_nm>MIKA KECIL</s_nm><s_price>0</s_price><sep/><s_nm>4.0xITEMS</s_nm><s_price>117,000</s_price></s_menu><s_sub_total><s_subtotal_price>117,000</s_subtotal_price><s_tax_price>11,700</s_tax_price></s_sub_total><s_total><s_total_price>128,700</s_total_price><s_cashprice>20,000</s_cashprice><s_changeprice>88,700</s_changeprice></s_total>\n",
            "    Answer: <s_menu><s_nm>TALAM UNGU</s_nm><s_unitprice>@6500</s_unitprice><s_cnt>3X</s_cnt><s_discountprice>-7,800</s_discountprice><s_price>19,500</s_price><sep/><s_nm>MIKA KECIL</s_nm><s_unitprice>@0</s_unitprice><s_cnt>1X</s_cnt><s_price>0</s_price></s_menu><s_sub_total><s_subtotal_price>11,700</s_subtotal_price></s_sub_total><s_total><s_total_price>11,700</s_total_price><s_cashprice>20,000</s_cashprice><s_changeprice>8,300</s_changeprice><s_menuqty_cnt>4.00xITEMs</s_menuqty_cnt></s_total>\n",
            " Normed ED: 0.3436213991769547\n",
            "Epoch 0: 100%|██████████| 400/400 [07:46<00:00,  0.86it/s, v_num=gio6]Pushing model to the hub, epoch 0\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/home/niels/python_projects/transformers/src/transformers/models/llava/configuration_llava.py:143: FutureWarning: The `vocab_size` attribute is deprecated and will be removed in v4.42, Please use `text_config.vocab_size` instead.\n",
            "  warnings.warn(\n",
            "/home/niels/python_projects/transformers/src/transformers/models/llava/configuration_llava.py:103: FutureWarning: The `vocab_size` argument is deprecated and will be removed in v4.42, since it can be inferred from the `text_config`. Passing this argument has no effect\n",
            "  warnings.warn(\n",
            "\n",
            "\u001b[A\n",
            "\u001b[A\n",
            "\u001b[A\n",
            "\u001b[A\n",
            "\u001b[A\n",
            "\u001b[A\n",
            "\u001b[A\n",
            "\u001b[A\n",
            "\u001b[A\n",
            "\u001b[A\n",
            "\u001b[A\n",
            "\u001b[A\n",
            "\u001b[A\n",
            "\u001b[A\n",
            "\u001b[A\n",
            "adapter_model.safetensors: 100%|██████████| 84.8M/84.8M [00:03<00:00, 21.5MB/s]\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Epoch 1: 100%|██████████| 400/400 [05:30<00:00,  1.21it/s, v_num=gio6]Prediction: <s_menu><s_nm>REAL GANACHE</s_nm><s_cnt>1</s_cnt><s_price>16,500</s_price><sep/><s_nm>EGG TART</s_nm><s_cnt>1</s_cnt><s_price>13,000</s_price><sep/><s_nm>PIZZA TOAST</s_nm><s_cnt>1</s_cnt><s_price>16,000</s_price></s_menu><s_total><s_total_price>45,500</s_total_price><s_cashprice>50,000</s_cashprice><s_changeprice>4,500</s_changeprice></s_total>\n",
            "    Answer: <s_menu><s_nm>REAL GANACHE</s_nm><s_cnt>1</s_cnt><s_price>16,500</s_price><sep/><s_nm>EGG TART</s_nm><s_cnt>1</s_cnt><s_price>13,000</s_price><sep/><s_nm>PIZZA TOAST</s_nm><s_cnt>1</s_cnt><s_price>16,000</s_price></s_menu><s_total><s_total_price>45,500</s_total_price><s_cashprice>50,000</s_cashprice><s_changeprice>4,500</s_changeprice></s_total>\n",
            " Normed ED: 0.0\n",
            "Prediction: <s_menu><s_nm>S-Ovaltime</s_nm><s_cnt>1</s_cnt><s_price>20,000</s_price></s_menu><s_sub_total><s_subtotal_price>20,000</s_subtotal_price><s_tax_price>1,818</s_tax_price></s_sub_total><s_total><s_total_price>21,818</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>78,182</s_changeprice><s_menutype_cnt>1.50</s_menutype_cnt></s_total>\n",
            "    Answer: <s_menu><s_nm>S-Ovaltine 50%</s_nm><s_unitprice>20,000</s_unitprice><s_cnt>1</s_cnt><s_price>20,000</s_price><s_vatyn>10% Tax Included</s_vatyn></s_menu><s_sub_total><s_subtotal_price>18,181</s_subtotal_price><s_tax_price>1,818</s_tax_price></s_sub_total><s_total><s_total_price>20,000</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>80,000</s_changeprice></s_total>\n",
            " Normed ED: 0.32460732984293195\n",
            "Prediction: <s_menu><s_nm>BBQ Chicken</s_nm><s_cnt>1</s_cnt><s_price>41,000</s_price><s_sub><s_nm>- Sedang</s_nm><s_cnt>1</s_cnt><s_price>0</s_price></s_sub></s_menu><s_sub_total><s_subtotal_price>41,000</s_subtotal_price></s_sub_total><s_total><s_total_price>41,000</s_total_price><s_cashprice>50,000</s_cashprice><s_changeprice>9,000</s_changeprice><s_menuqty_cnt>1</s_menuqty_cnt></s_total>\n",
            "    Answer: <s_menu><s_nm>BBQ Chicken</s_nm><s_cnt>1</s_cnt><s_price>41,000</s_price><s_sub><s_nm>Sedang</s_nm><s_cnt>1</s_cnt><s_price>0</s_price></s_sub></s_menu><s_sub_total><s_subtotal_price>41,000</s_subtotal_price></s_sub_total><s_total><s_total_price>41,000</s_total_price><s_cashprice>50.000</s_cashprice><s_changeprice>:9,000</s_changeprice><s_menuqty_cnt>1</s_menuqty_cnt></s_total>\n",
            " Normed ED: 0.010498687664041995\n",
            "Prediction: <s_menu><s_nm>POTATO SAUSAGE BREAD</s_nm><s_cnt>1</s_cnt><s_price>19,000</s_price><sep/><s_nm>OREO GREEN TEA SPREAD</s_nm><s_cnt>1</s_cnt><s_price>19,000</s_price><sep/><s_nm>WHITE CHOCO BANANA SPREAD</s_nm><s_cnt>1</s_cnt><s_price>22,000</s_price></s_menu><s_total><s_total_price>123,000</s_total_price><s_creditcardprice>123,000</s_creditcardprice></s_total>\n",
            "    Answer: <s_menu><s_nm>POTATO SAUSAGE BREAD</s_nm><s_cnt>1</s_cnt><s_price>19,000</s_price><sep/><s_nm>OREO GREEN TEA SPREAD</s_nm><s_cnt>1</s_cnt><s_price>52,000</s_price><sep/><s_nm>WHITE CHOCO BANANA SPREAD</s_nm><s_cnt>1</s_cnt><s_price>52,000</s_price></s_menu><s_total><s_total_price>123,000</s_total_price><s_creditcardprice>123,000</s_creditcardprice></s_total>\n",
            " Normed ED: 0.008333333333333333\n",
            "Prediction: <s_menu><s_nm>TALAHM UNGU</s_nm><s_discountprice>-7,800</s_discountprice><s_price>58,500</s_price><sep/><s_nm>MIKA KECIL</s_nm><s_price>0</s_price><sep/><s_nm>4XITEMS</s_nm><s_price>0</s_price></s_menu><s_sub_total><s_subtotal_price>11,700</s_subtotal_price></s_sub_total><s_total><s_total_price>11,700</s_total_price><s_cashprice>20,000</s_cashprice><s_changeprice>8,300</s_changeprice></s_total>\n",
            "    Answer: <s_menu><s_nm>TALAM UNGU</s_nm><s_unitprice>@6500</s_unitprice><s_cnt>3X</s_cnt><s_discountprice>-7,800</s_discountprice><s_price>19,500</s_price><sep/><s_nm>MIKA KECIL</s_nm><s_unitprice>@0</s_unitprice><s_cnt>1X</s_cnt><s_price>0</s_price></s_menu><s_sub_total><s_subtotal_price>11,700</s_subtotal_price></s_sub_total><s_total><s_total_price>11,700</s_total_price><s_cashprice>20,000</s_cashprice><s_changeprice>8,300</s_changeprice><s_menuqty_cnt>4.00xITEMs</s_menuqty_cnt></s_total>\n",
            " Normed ED: 0.24074074074074073\n",
            "Epoch 1: 100%|██████████| 400/400 [07:39<00:00,  0.87it/s, v_num=gio6]Pushing model to the hub, epoch 1\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n",
            "\u001b[A\n",
            "\u001b[A\n",
            "\u001b[A\n",
            "\u001b[A\n",
            "\u001b[A\n",
            "\u001b[A\n",
            "\u001b[A\n",
            "\u001b[A\n",
            "\u001b[A\n",
            "\u001b[A\n",
            "\u001b[A\n",
            "\u001b[A\n",
            "\u001b[A\n",
            "\u001b[A\n",
            "\u001b[A\n",
            "\u001b[A\n",
            "\u001b[A\n",
            "adapter_model.safetensors: 100%|██████████| 84.8M/84.8M [00:04<00:00, 18.5MB/s]\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Epoch 1: 100%|██████████| 400/400 [07:46<00:00,  0.86it/s, v_num=gio6]"
          ]
        }
      ],
      "source": [
        "from lightning.pytorch.loggers import WandbLogger\n",
        "\n",
        "wandb_logger = WandbLogger(project=WANDB_PROJECT, name=WANDB_NAME)\n",
        "\n",
        "trainer = L.Trainer(\n",
        "        accelerator=\"gpu\",\n",
        "        devices=[0],\n",
        "        max_epochs=config.get(\"max_epochs\"),\n",
        "        accumulate_grad_batches=config.get(\"accumulate_grad_batches\"),\n",
        "        check_val_every_n_epoch=config.get(\"check_val_every_n_epoch\"),\n",
        "        gradient_clip_val=config.get(\"gradient_clip_val\"),\n",
        "        precision=\"16-mixed\",\n",
        "        limit_val_batches=5,\n",
        "        num_sanity_val_steps=0,\n",
        "        logger=wandb_logger,\n",
        "        callbacks=[PushToHubCallback(), early_stop_callback],\n",
        ")\n",
        "\n",
        "trainer.fit(model_module)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hQPiR5IV89qs"
      },
      "source": [
        "## Inference\n",
        "\n",
        "Let's see if the model has learned something. We'll load the model from the hub first. Notice that, as we only trained adapters on top of the base model, the [repository on the hub](https://huggingface.co/nielsr/idefics2-cord-demo) to which we pushed only contains the weights and configuration of the adapters. This is a very lightweight file smaller than 100 MB.\n",
        "\n",
        "Thanks to the PEFT integration in Transformers, the `from_pretrained` method will automatically load the weights of the base model as well as the adapter weights.\n",
        "\n",
        "To reduce inference costs, we'll again load the model in 4 bits by passing a `quantization_config`, in order to reduce memory usage."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "jc0JHzIY89qs",
        "outputId": "5845f9fb-0296-47b3-ad21-9dec3fb1093e"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n",
            "/home/niels/python_projects/transformers/src/transformers/models/llava/configuration_llava.py:103: FutureWarning: The `vocab_size` argument is deprecated and will be removed in v4.42, since it can be inferred from the `text_config`. Passing this argument has no effect\n",
            "  warnings.warn(\n",
            "`low_cpu_mem_usage` was None, now set to True since model is quantized.\n",
            "\n",
            "\u001b[A\n",
            "\u001b[A\n",
            "\u001b[A\n",
            "Loading checkpoint shards: 100%|██████████| 3/3 [00:24<00:00,  8.24s/it]\n"
          ]
        }
      ],
      "source": [
        "from transformers import AutoProcessor, BitsAndBytesConfig, LlavaForConditionalGeneration\n",
        "import torch\n",
        "\n",
        "processor = AutoProcessor.from_pretrained(MODEL_ID)\n",
        "\n",
        "# Define quantization config\n",
        "quantization_config = BitsAndBytesConfig(\n",
        "    load_in_4bit=True, bnb_4bit_quant_type=\"nf4\", bnb_4bit_compute_dtype=torch.float16\n",
        ")\n",
        "# Load the base model with adapters on top\n",
        "model = LlavaForConditionalGeneration.from_pretrained(\n",
        "    REPO_ID,\n",
        "    torch_dtype=torch.float16,\n",
        "    quantization_config=quantization_config,\n",
        ")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5Lqxte3U89qs"
      },
      "source": [
        "Now we're ready to perform inference. We'll take a receipt image of the test set here."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "BNw1jE0n89qw",
        "outputId": "f93b5f96-8565-4c78-b802-74195ae63d9c"
      },
      "outputs": [
        {
          "data": {
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",
            "image/png": 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",
            "text/plain": [
              "<PIL.PngImagePlugin.PngImageFile image mode=RGB size=432x648>"
            ]
          },
          "execution_count": 22,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "test_example = dataset[\"test\"][0]\n",
        "test_image = test_example[\"image\"]\n",
        "test_image"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xWWHU1xB89qx"
      },
      "source": [
        "Next we need to prepare the image for the model, along with the text prompt we used during training. We need to apply the chat template to make sure the format is respected.\n",
        "\n",
        "Notice that this is exactly the same as what we did for the evaluation data collate function."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "BBWCEdiT89qx",
        "outputId": "3d36269e-c9b7-43e2-85ad-1500c62f146d"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "input_ids torch.Size([1, 17])\n",
            "attention_mask torch.Size([1, 17])\n",
            "pixel_values torch.Size([1, 3, 336, 336])\n"
          ]
        }
      ],
      "source": [
        "# prepare image and prompt for the model\n",
        "# TODO this can be replaced by apply_chat_template when the processor supports this\n",
        "prompt = f\"USER: <image>\\nExtract JSON.\\nASSISTANT:\"\n",
        "inputs = processor(text=prompt, images=[test_image], return_tensors=\"pt\").to(\"cuda\")\n",
        "for k,v in inputs.items():\n",
        "    print(k,v.shape)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "w2Brzvy689qx"
      },
      "source": [
        "Next we let the model autoregressively generate tokens using the [generate()](https://huggingface.co/docs/transformers/v4.40.1/en/main_classes/text_generation#transformers.GenerationMixin.generate) method, which is recommended for use at inference time. This method feeds each predicted token back into the model as conditioning for each next time step.\n",
        "\n",
        "Do note that there are various ways of decoding text, here we use greedy decoding which is the default. There are various fancier methods such as beam search and top-k sampling. Refer to [this amazing blog post](https://huggingface.co/blog/how-to-generate) for all details."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "xFSVXwN889qx"
      },
      "outputs": [],
      "source": [
        "# Generate token IDs\n",
        "generated_ids = model.generate(**inputs, max_new_tokens=MAX_LENGTH)\n",
        "\n",
        "# Decode back into text\n",
        "generated_texts = processor.batch_decode(generated_ids, skip_special_tokens=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Bn5yop6589qx",
        "outputId": "537adbf4-56b6-4513-dbb5-58ba0adaa898"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "['USER:  \\nExtract JSON.\\nASSISTANT: <s_menu><s_nm>TICKET CP</s_nm><s_num>901016</s_num><s_unitprice>60.000</s_unitprice><s_cnt>2</s_cnt><s_discountprice>-60.000</s_discountprice><s_price>60.000</s_price></s_menu><s_sub_total><s_subtotal_price>60.000</s_subtotal_price><s_tax_price>5,455</s_tax_price></s_sub_total><s_total><s_total_price>65.455</s_total_price><s_cashprice>65.455</s_cashprice></s_total>']\n"
          ]
        }
      ],
      "source": [
        "print(generated_texts)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uczAL04v89qx"
      },
      "source": [
        "Based on the Donut model, we could write a `token2json` method which converts the generated token sequence into parsible JSON."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ELwUILkk89qx"
      },
      "outputs": [],
      "source": [
        "import re\n",
        "\n",
        "# let's turn that into JSON\n",
        "def token2json(tokens, is_inner_value=False, added_vocab=None):\n",
        "        \"\"\"\n",
        "        Convert a (generated) token sequence into an ordered JSON format.\n",
        "        \"\"\"\n",
        "        if added_vocab is None:\n",
        "            added_vocab = processor.tokenizer.get_added_vocab()\n",
        "\n",
        "        output = {}\n",
        "\n",
        "        while tokens:\n",
        "            start_token = re.search(r\"<s_(.*?)>\", tokens, re.IGNORECASE)\n",
        "            if start_token is None:\n",
        "                break\n",
        "            key = start_token.group(1)\n",
        "            key_escaped = re.escape(key)\n",
        "\n",
        "            end_token = re.search(rf\"</s_{key_escaped}>\", tokens, re.IGNORECASE)\n",
        "            start_token = start_token.group()\n",
        "            if end_token is None:\n",
        "                tokens = tokens.replace(start_token, \"\")\n",
        "            else:\n",
        "                end_token = end_token.group()\n",
        "                start_token_escaped = re.escape(start_token)\n",
        "                end_token_escaped = re.escape(end_token)\n",
        "                content = re.search(\n",
        "                    f\"{start_token_escaped}(.*?){end_token_escaped}\", tokens, re.IGNORECASE | re.DOTALL\n",
        "                )\n",
        "                if content is not None:\n",
        "                    content = content.group(1).strip()\n",
        "                    if r\"<s_\" in content and r\"</s_\" in content:  # non-leaf node\n",
        "                        value = token2json(content, is_inner_value=True, added_vocab=added_vocab)\n",
        "                        if value:\n",
        "                            if len(value) == 1:\n",
        "                                value = value[0]\n",
        "                            output[key] = value\n",
        "                    else:  # leaf nodes\n",
        "                        output[key] = []\n",
        "                        for leaf in content.split(r\"<sep/>\"):\n",
        "                            leaf = leaf.strip()\n",
        "                            if leaf in added_vocab and leaf[0] == \"<\" and leaf[-2:] == \"/>\":\n",
        "                                leaf = leaf[1:-2]  # for categorical special tokens\n",
        "                            output[key].append(leaf)\n",
        "                        if len(output[key]) == 1:\n",
        "                            output[key] = output[key][0]\n",
        "\n",
        "                tokens = tokens[tokens.find(end_token) + len(end_token) :].strip()\n",
        "                if tokens[:6] == r\"<sep/>\":  # non-leaf nodes\n",
        "                    return [output] + token2json(tokens[6:], is_inner_value=True, added_vocab=added_vocab)\n",
        "\n",
        "        if len(output):\n",
        "            return [output] if is_inner_value else output\n",
        "        else:\n",
        "            return [] if is_inner_value else {\"text_sequence\": tokens}"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1auSQSQ389qx"
      },
      "source": [
        "Let's print the final JSON!"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "gyolG3Hj89qx",
        "outputId": "24f00755-118a-4865-fd28-7306a30e3484"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "{'menu': {'nm': 'TICKET CP', 'num': '901016', 'unitprice': '60.000', 'cnt': '2', 'discountprice': '-60.000', 'price': '60.000'}, 'sub_total': {'subtotal_price': '60.000', 'tax_price': '5,455'}, 'total': {'total_price': '65.455', 'cashprice': '65.455'}}\n"
          ]
        }
      ],
      "source": [
        "generated_json = token2json(generated_texts[0])\n",
        "print(generated_json)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "1DczSOBQ89qx",
        "outputId": "c4732ebc-a037-424c-c599-83e90d3dd4ab"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "menu {'nm': 'TICKET CP', 'num': '901016', 'unitprice': '60.000', 'cnt': '2', 'discountprice': '-60.000', 'price': '60.000'}\n",
            "sub_total {'subtotal_price': '60.000', 'tax_price': '5,455'}\n",
            "total {'total_price': '65.455', 'cashprice': '65.455'}\n"
          ]
        }
      ],
      "source": [
        "for key, value in generated_json.items():\n",
        "    print(key, value)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "bKS_QcmX89qx"
      },
      "outputs": [],
      "source": []
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "env",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.8.10"
    },
    "colab": {
      "provenance": [],
      "include_colab_link": true
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}